metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-brain-tumor-detection3
results: []
vit-base-brain-tumor-detection3
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3419
- Accuracy: 0.9406
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0048 | 7.8125 | 500 | 0.2337 | 0.9473 |
| 0.0012 | 15.625 | 1000 | 0.1950 | 0.9531 |
| 0.0007 | 23.4375 | 1500 | 0.1927 | 0.9580 |
| 0.0004 | 31.25 | 2000 | 0.1970 | 0.9629 |
| 0.0003 | 39.0625 | 2500 | 0.2040 | 0.9629 |
| 0.0002 | 46.875 | 3000 | 0.2114 | 0.9629 |
| 0.0002 | 54.6875 | 3500 | 0.2171 | 0.9648 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1